{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5e91de8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dcff8f71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>性别</th>\n",
       "      <th>入学专业</th>\n",
       "      <th>现在专业</th>\n",
       "      <th>GPA-2018-2019</th>\n",
       "      <th>论文情况-1819</th>\n",
       "      <th>阅读情况</th>\n",
       "      <th>荣誉情况</th>\n",
       "      <th>活动分数</th>\n",
       "      <th>2018-体测</th>\n",
       "      <th>类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>['女']</td>\n",
       "      <td>['物联网工程']</td>\n",
       "      <td>['物联网工程']</td>\n",
       "      <td>3.818125</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.15</td>\n",
       "      <td>学校奖学金三等奖学金</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>['男']</td>\n",
       "      <td>['通信工程（+人工智能，大类招生）']</td>\n",
       "      <td>['通信工程信息与通信工程学科“英才班”']</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>无</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>['男']</td>\n",
       "      <td>['物联网工程']</td>\n",
       "      <td>['物联网工程']</td>\n",
       "      <td>2.595625</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>83.60</td>\n",
       "      <td>学校奖学金三等奖学金</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>['男']</td>\n",
       "      <td>['计算机科学与技术']</td>\n",
       "      <td>['智能科学与技术']</td>\n",
       "      <td>2.106789</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.50</td>\n",
       "      <td>无</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>['男']</td>\n",
       "      <td>['物联网工程']</td>\n",
       "      <td>['物联网工程']</td>\n",
       "      <td>3.574792</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>76.30</td>\n",
       "      <td>学校奖学金一等奖学金</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0     性别                  入学专业                    现在专业  \\\n",
       "0           0  ['女']             ['物联网工程']               ['物联网工程']   \n",
       "1           1  ['男']  ['通信工程（+人工智能，大类招生）']  ['通信工程信息与通信工程学科“英才班”']   \n",
       "2           2  ['男']             ['物联网工程']               ['物联网工程']   \n",
       "3           3  ['男']          ['计算机科学与技术']             ['智能科学与技术']   \n",
       "4           4  ['男']             ['物联网工程']               ['物联网工程']   \n",
       "\n",
       "   GPA-2018-2019  论文情况-1819  阅读情况  荣誉情况  活动分数  2018-体测          类型  \n",
       "0       3.818125          0     7     1   0.0    72.15  学校奖学金三等奖学金  \n",
       "1       0.000000          0    21     1  23.0     0.00           无  \n",
       "2       2.595625          0     6     2   0.0    83.60  学校奖学金三等奖学金  \n",
       "3       2.106789          0     0     0   0.0    72.50           无  \n",
       "4       3.574792          0    29     4   5.0    76.30  学校奖学金一等奖学金  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"18-19train_update.csv\",low_memory=False,usecols=list_a)\n",
    "p1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e22fba81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1349\n",
      "5557\n"
     ]
    }
   ],
   "source": [
    "get_award=0\n",
    "lose_award=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        lose_award=lose_award+1\n",
    "    elif get!=\"无\":\n",
    "        get_award=get_award+1\n",
    "print(get_award)\n",
    "print(lose_award)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fa1a1db4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p1[\"GPA-2018-2019\"][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "aa88258d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1346\n",
      "1874\n"
     ]
    }
   ],
   "source": [
    "with_award=[]\n",
    "no_award=[]\n",
    "get_count_wisdom=0\n",
    "lose_count_wisdom=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        if p1[\"GPA-2018-2019\"][i]>0:\n",
    "            no_award.append(p1[\"GPA-2018-2019\"][i])\n",
    "            lose_count_wisdom=lose_count_wisdom+1\n",
    "    elif get!=\"无\":\n",
    "         if p1[\"GPA-2018-2019\"][i]>0:\n",
    "            with_award.append(p1[\"GPA-2018-2019\"][i])\n",
    "            get_count_wisdom=get_count_wisdom+1\n",
    "\n",
    "print(get_count_wisdom)\n",
    "print(lose_count_wisdom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "be1891dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2018-2019获奖与未获奖的学生GPA成绩分布\n",
    "get_averge_GPA='{:.2f}'.format(np.mean(with_award))\n",
    "no_averge_GPA='{:.2f}'.format(np.mean(no_award))\n",
    "get_std_GPA='{:.2f}'.format(np.std(with_award))\n",
    "no_std_GPA='{:.2f}'.format(np.std(no_award))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('18-19学年获奖与未获奖GPA分布直方图',fontsize=20)\n",
    "plt.xlabel('GPA',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "plt.hist(no_award,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_GPA)+\"   方差：\"+str(no_std_GPA),color=\"steelblue\")\n",
    "plt.hist(with_award,bins=100,label=\"获得奖学金   均值：\"+str(get_averge_GPA)+\"   方差：\"+str(get_std_GPA),color=\"purple\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e91d3abc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2019-2020获奖与未获奖的学生GPA成绩分布\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"19-20train_update.csv\",low_memory=False,usecols=list_a)\n",
    "p1.head()\n",
    "with_award=[]\n",
    "no_award=[]\n",
    "get_count_wisdom=0\n",
    "lose_count_wisdom=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        if p1[\"GPA-2019-2020\"][i]>0:\n",
    "            no_award.append(p1[\"GPA-2019-2020\"][i])\n",
    "            lose_count_wisdom=lose_count_wisdom+1\n",
    "    elif get!=\"无\":\n",
    "         if p1[\"GPA-2019-2020\"][i]>0:\n",
    "            with_award.append(p1[\"GPA-2019-2020\"][i])\n",
    "            get_count_wisdom=get_count_wisdom+1\n",
    "get_averge_GPA='{:.2f}'.format(np.mean(with_award))\n",
    "no_averge_GPA='{:.2f}'.format(np.mean(no_award))\n",
    "get_std_GPA='{:.2f}'.format(np.std(with_award))\n",
    "no_std_GPA='{:.2f}'.format(np.std(no_award))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('19-20学年获奖与未获奖GPA分布直方图',fontsize=20)\n",
    "plt.xlabel('GPA',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "plt.hist(no_award,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_GPA)+\"   方差：\"+str(no_std_GPA),color=\"steelblue\")\n",
    "plt.hist(with_award,bins=100,label=\"获得奖学金   均值：\"+str(get_averge_GPA)+\"   方差：\"+str(get_std_GPA),color=\"purple\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "\n",
    "plt.show()\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6a86a181",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2020-2021获奖与未获奖的学生GPA成绩分布\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"20-21train_update.csv\",low_memory=False,usecols=list_a)\n",
    "p1.head()\n",
    "with_award=[]\n",
    "no_award=[]\n",
    "get_count_wisdom=0\n",
    "lose_count_wisdom=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        if p1[\"GPA-2020-2021\"][i]>0:\n",
    "            no_award.append(p1[\"GPA-2020-2021\"][i])\n",
    "            lose_count_wisdom=lose_count_wisdom+1\n",
    "    elif get!=\"无\":\n",
    "         if p1[\"GPA-2020-2021\"][i]>0:\n",
    "            with_award.append(p1[\"GPA-2020-2021\"][i])\n",
    "            get_count_wisdom=get_count_wisdom+1\n",
    "get_averge_GPA='{:.2f}'.format(np.mean(with_award))\n",
    "no_averge_GPA='{:.2f}'.format(np.mean(no_award))\n",
    "get_std_GPA='{:.2f}'.format(np.std(with_award))\n",
    "no_std_GPA='{:.2f}'.format(np.std(no_award))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('20-21学年获奖与未获奖GPA分布直方图',fontsize=20)\n",
    "plt.xlabel('GPA',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "plt.hist(no_award,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_GPA)+\"   方差：\"+str(no_std_GPA),color=\"steelblue\")\n",
    "plt.hist(with_award,bins=100,label=\"获得奖学金   均值：\"+str(get_averge_GPA)+\"   方差：\"+str(get_std_GPA),color=\"purple\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "\n",
    "plt.show()\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8d3fd9d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7514526901578182"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "me=np.std(no_award)\n",
    "me"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "79b12850",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1347\n",
      "1889\n"
     ]
    }
   ],
   "source": [
    "# 绘制2018-2019获奖与未获奖的学生体测成绩分布\n",
    "# type(p1[\"类型\"][0])\n",
    "with_award_pe=[]\n",
    "no_award_pe=[]\n",
    "get_count_pe=0\n",
    "lose_count_pe=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        if p1[\"2018-体测\"][i]>0:\n",
    "            no_award_pe.append(p1[\"2018-体测\"][i])\n",
    "            lose_count_pe=lose_count_pe+1\n",
    "    elif get!=\"无\":\n",
    "         if p1[\"2018-体测\"][i]>0:\n",
    "            with_award_pe.append(p1[\"2018-体测\"][i])\n",
    "            get_count_pe=get_count_pe+1\n",
    "# 绘制2018-2019获奖与未获奖的学生体测成绩分布\n",
    "with_averge_pe='{:.2f}'.format(np.mean(with_award_pe))\n",
    "no_averge_pe='{:.2f}'.format(np.mean(no_award_pe))\n",
    "with_std_pe='{:.2f}'.format(np.std(with_award_pe))\n",
    "no_std_pe='{:.2f}'.format(np.std(no_award_pe))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('18-19学年获奖与未获奖体测成绩分布直方图',fontsize=20)\n",
    "plt.xlabel('体测成绩',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "plt.hist(no_award_pe,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_pe)+\"   方差：\"+str(no_std_pe),color=\"steelblue\")\n",
    "plt.hist(with_award_pe,bins=100,label=\"获得奖学金   均值：\"+str(with_averge_pe)+\"   方差：\"+str(with_std_pe),color=\"purple\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "plt.show()     \n",
    "print(get_count_pe)\n",
    "print(lose_count_pe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "50d59231",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2019-2020获奖与未获奖的学生体测成绩分布\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"19-20train_update.csv\",low_memory=False,usecols=list_a)\n",
    "with_award_pe=[]\n",
    "no_award_pe=[]\n",
    "get_count_pe=0\n",
    "lose_count_pe=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        if p1[\"2019-体测\"][i]>0:\n",
    "            no_award_pe.append(p1[\"2019-体测\"][i])\n",
    "            lose_count_pe=lose_count_pe+1\n",
    "    elif get!=\"无\":\n",
    "         if p1[\"2019-体测\"][i]>0:\n",
    "            with_award_pe.append(p1[\"2019-体测\"][i])\n",
    "            get_count_pe=get_count_pe+1\n",
    "# 绘制2018-2019获奖与未获奖的学生体测成绩分布\n",
    "with_averge_pe='{:.2f}'.format(np.mean(with_award_pe))\n",
    "no_averge_pe='{:.2f}'.format(np.mean(no_award_pe))\n",
    "with_std_pe='{:.2f}'.format(np.std(with_award_pe))\n",
    "no_std_pe='{:.2f}'.format(np.std(no_award_pe))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('19-20学年获奖与未获奖体测成绩分布直方图',fontsize=20)\n",
    "plt.xlabel('体测成绩',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "plt.hist(no_award_pe,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_pe)+\"   方差：\"+str(no_std_pe),color=\"steelblue\")\n",
    "plt.hist(with_award_pe,bins=100,label=\"获得奖学金   均值：\"+str(with_averge_pe)+\"   方差：\"+str(with_std_pe),color=\"purple\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "plt.show()     \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fe62d184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2020-2021获奖与未获奖的学生体测成绩分布\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"20-21train_update.csv\",low_memory=False,usecols=list_a)\n",
    "with_award_pe=[]\n",
    "no_award_pe=[]\n",
    "get_count_pe=0\n",
    "lose_count_pe=0\n",
    "for i in range(0,6906):\n",
    "    get=p1[\"类型\"][i]\n",
    "    if get==\"无\":\n",
    "        if p1[\"2020-体测\"][i]>0:\n",
    "            no_award_pe.append(p1[\"2020-体测\"][i])\n",
    "            lose_count_pe=lose_count_pe+1\n",
    "    elif get!=\"无\":\n",
    "         if p1[\"2020-体测\"][i]>0:\n",
    "            with_award_pe.append(p1[\"2020-体测\"][i])\n",
    "            get_count_pe=get_count_pe+1\n",
    "# 绘制2018-2019获奖与未获奖的学生体测成绩分布\n",
    "with_averge_pe='{:.2f}'.format(np.mean(with_award_pe))\n",
    "no_averge_pe='{:.2f}'.format(np.mean(no_award_pe))\n",
    "with_std_pe='{:.2f}'.format(np.std(with_award_pe))\n",
    "no_std_pe='{:.2f}'.format(np.std(no_award_pe))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('20-21学年获奖与未获奖体测成绩分布直方图',fontsize=20)\n",
    "plt.xlabel('体测成绩',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "plt.hist(no_award_pe,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_pe)+\"   方差：\"+str(no_std_pe),color=\"steelblue\")\n",
    "plt.hist(with_award_pe,bins=100,label=\"获得奖学金   均值：\"+str(with_averge_pe)+\"   方差：\"+str(with_std_pe),color=\"purple\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "plt.show()     \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1b46b5fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制三年来学生体测成绩分布变化情况\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"18-19train_update.csv\",low_memory=False,usecols=list_a)\n",
    "p2=pd.read_csv(\"19-20train_update.csv\",low_memory=False,usecols=list_a)\n",
    "p3=pd.read_csv(\"20-21train_update.csv\",low_memory=False,usecols=list_a)\n",
    "total_first=[]\n",
    "total_second=[]\n",
    "total_third=[]\n",
    "# with_award_pe=[]\n",
    "# no_award_pe=[]\n",
    "# get_count_pe=0\n",
    "# lose_count_pe=0\n",
    "for i in range(0,6906):\n",
    "    if p1[\"2018-体测\"][i]>0:\n",
    "        total_first.append(p1[\"2018-体测\"][i])\n",
    "    if p2[\"2019-体测\"][i]>0:\n",
    "        total_second.append(p2[\"2019-体测\"][i])\n",
    "    if p3[\"2020-体测\"][i]>0:\n",
    "        total_third.append(p3[\"2020-体测\"][i])\n",
    "    \n",
    "# 绘制2018-2019所有学生的体测成绩分布\n",
    "total_first_averge_pe='{:.2f}'.format(np.mean(total_first))\n",
    "# no_averge_pe='{:.2f}'.format(np.mean(no_award_pe))\n",
    "total_first_std_pe='{:.2f}'.format(np.std(total_first))\n",
    "# no_std_pe='{:.2f}'.format(np.std(no_award_pe))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('18-19学年学生体测成绩分布直方图',fontsize=20)\n",
    "plt.xlabel('体测成绩',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "# plt.hist(no_award_pe,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_pe)+\"   方差：\"+str(no_std_pe),color=\"steelblue\")\n",
    "plt.hist(total_first,bins=100,label=\"体测成绩均值：\"+str(total_first_averge_pe)+\"   方差：\"+str(total_first_std_pe),color=\"steelblue\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "plt.show()     \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3d96e934",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2019-2020所有学生的体测成绩分布\n",
    "total_second_averge_pe='{:.2f}'.format(np.mean(total_second))\n",
    "# no_averge_pe='{:.2f}'.format(np.mean(no_award_pe))\n",
    "total_second_std_pe='{:.2f}'.format(np.std(total_second))\n",
    "# no_std_pe='{:.2f}'.format(np.std(no_award_pe))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('19-20学年学生体测成绩分布直方图',fontsize=20)\n",
    "plt.xlabel('体测成绩',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "# plt.hist(no_award_pe,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_pe)+\"   方差：\"+str(no_std_pe),color=\"steelblue\")\n",
    "plt.hist(total_second,bins=100,label=\"体测成绩均值：\"+str(total_second_averge_pe)+\"   方差：\"+str(total_second_std_pe),color=\"steelblue\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "plt.show()     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c1ac86d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制2020-2021所有学生的体测成绩分布\n",
    "total_third_averge_pe='{:.2f}'.format(np.mean(total_third))\n",
    "# no_averge_pe='{:.2f}'.format(np.mean(no_award_pe))\n",
    "total_third_std_pe='{:.2f}'.format(np.std(total_third))\n",
    "# no_std_pe='{:.2f}'.format(np.std(no_award_pe))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.figure(figsize=(12,5))\n",
    "plt.title('20-21学年学生体测成绩分布直方图',fontsize=20)\n",
    "plt.xlabel('体测成绩',fontsize=15)\n",
    "plt.ylabel('人数',fontsize=15)\n",
    "# plt.hist(no_award_pe,bins=100,label=\"未获奖学金   均值：\"+str(no_averge_pe)+\"   方差：\"+str(no_std_pe),color=\"steelblue\")\n",
    "plt.hist(total_third,bins=100,label=\"体测成绩均值：\"+str(total_third_averge_pe)+\"   方差：\"+str(total_third_std_pe),color=\"steelblue\")\n",
    "# 显示图例\n",
    "plt.legend(loc='best',fontsize=15)\n",
    "plt.show()     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "80e7edb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['通信工程']                  757\n",
       "['计算机科学与技术']              693\n",
       "['电信工程及管理']               576\n",
       "['信息工程']                  467\n",
       "['电子商务及法律']               338\n",
       "['物联网工程']                 331\n",
       "['软件工程']                  295\n",
       "['电子科学与技术']               251\n",
       "['光电信息科学与工程']             157\n",
       "['网络空间安全']                147\n",
       "['电子信息工程']                139\n",
       "['自动化']                   132\n",
       "['智能科学与技术']               129\n",
       "['通信工程信息与通信工程学科“英才班”']    122\n",
       "['网络工程']                  122\n",
       "['数字媒体技术']                121\n",
       "['信息管理与信息系统']             115\n",
       "['邮政工程（互联网与智慧物流）']        115\n",
       "['电子信息科学与技术（+AI）']        114\n",
       "['应用物理学']                 114\n",
       "['数据科学与大数据技术']            112\n",
       "['信息安全']                  110\n",
       "['测控技术与仪器']                96\n",
       "['英语']                     93\n",
       "['电子信息科学与技术']              89\n",
       "['法学']                     66\n",
       "['信息与计算科学']                66\n",
       "['邮政管理（互联网与智慧物流）']         66\n",
       "['数字媒体艺术']                 61\n",
       "['机械工程（机器人试验班）']           61\n",
       "['机械工程']                   59\n",
       "['电子商务']                   56\n",
       "['工业设计（智能与信息交互设计）']        52\n",
       "['公共事业管理']                 51\n",
       "['数学与应用数学']                51\n",
       "['电磁场与无线技术']               46\n",
       "['工业设计']                   42\n",
       "['网络空间安全（实验班）']            40\n",
       "['经济学专业（经济学方向）']           39\n",
       "['会计学']                    38\n",
       "['国际经济与贸易']                37\n",
       "['日语']                     37\n",
       "['工商管理专业（会计学方向）']          34\n",
       "['经济学']                    33\n",
       "['信息安全（双培）']               30\n",
       "['电子信息工程大数据及信息处理（双培）']     29\n",
       "['通信工程5G通信技术（双培）']         28\n",
       "['通信工程（+人工智能，大类招生）']       28\n",
       "['材料科学与工程']                24\n",
       "['工商管理专业（工商管理方向）']         21\n",
       "['计算机科学与技术（实验班）']          19\n",
       "['信息与通信工程学科实验班']           19\n",
       "['电子商务双培（互联网商务方向）']        15\n",
       "['电子工程学院实验班（光电子方向）']        9\n",
       "['电子工程学院实验班（微电子方向）']        7\n",
       "['电子商务双培（互联网物流方向）']         7\n",
       "Name: 现在专业, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ast\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "list_a=np.arange(11)\n",
    "p1=pd.read_csv(\"18-19train_update.csv\",low_memory=False,usecols=list_a)\n",
    "p1[\"现在专业\"].value_counts()\n",
    "# p1[\"现在专业\"].unique()\n",
    "# p1[\"现在专业\"].unique()[0]==\"['物联网工程']\"\n",
    "# p1[\"现在专业\"].nunique()\n",
    "# p1[\"现在专业\"].unique()[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d74d7e67",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a144acaa",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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